Given a set of mixed spectral (multispectral or hyperspectral) vectors, linear spectral mixture analysis, or linear unmixing, aims at estimating the number of reference substances, also called endmembers, their spectral signatures, and their abundance fractions. This paper presents a new method for unsupervised endmember extraction from hyperspectral data, termed vertex component analysis (VCA). The algorithm exploits two facts: (1) the endmembers are the vertices of a simplex and (2) the affine transformation of a simplex is also a simplex. In a series of experiments using simulated and real data, the VCA algorithm competes with state-of-the-art methods, with a computational complexity between one and two orders of magnitude lower than the best available method.

/pdf/vertex-component-analysis-a-fast-algorithm-to-unmix-1egulrpm76.pdf

Vertex component analysis: a fast algorithm to unmix hyperspectral data

https://www.whoi.edu/cms/files/Ecological_Modelling_2002_Boyce_53558.pdf

Evaluating resource selection functions

https://www.ipcc-nggip.iges.or.jp/public/gpglulucf/gpglulucf_files/0_Task1_Cover/Cover_TOC.pdf

Good Practice Guidance for Land Use, Land-Use Change and Forestry

Vegetation phenological phenomena are closely related to seasonal dynamics of the lower atmosphere and are therefore important elements in global models and vegetation monitoring. Normalized difference vegetation index (NDVI) data derived from the National Oceanic and Atmospheric Administration's Advanced Very High Resolution Radiom- eter (AVHRR) satellite sensor offer a means of efficiently and objectively evaluating phenological characteristics over large areas. Twelve metrics linked to key phenological events were computed based on time-series NDVI data collected from 1989 to 1992 over the conterminous United States. These measures include the onset of greenness, time of peak NDVI, maximum NDVI, rate of greenup, rate of senescence, and integrated NDVI. Measures of central tendency and variabil- ity of the measures were computed and analyzed for various land cover types. Results from the analysis showed strong coincidence between the satellite-derived metrics and pre- dicted phenological characteristics. In particular, the metrics identified interannual variability of spring wheat in North Dakota, characterized the phenology of four types of grasslands, and established the phenological consistency of deciduous and coniferous forests. These results have implications for large- area land cover mapping and monitoring. The utility of re- motely sensed data as input to vegetation mapping is demon- strated by showing the distinct phenology of several land cover types. More stable information contained in ancillary data should be incorporated into the mapping process, particu- larly in areas with high phenological variability. In a regional or global monitoring system, an increase in variability in a region may serve as a signal to perform more detailed land cover analysis with higher resolution imagery.

Measuring phenological variability from satellite imagery

The amount of scientific literature on (Geographic) Object-based Image Analysis – GEOBIA has been and still is sharply increasing. These approaches to analysing imagery have antecedents in earlier research on image segmentation and use GIS-like spatial analysis within classification and feature extraction approaches. This article investigates these development and its implications and asks whether or not this is a new paradigm in remote sensing and Geographic Information Science (GIScience). We first discuss several limitations of prevailing per-pixel methods when applied to high resolution images. Then we explore the paradigm concept developed by Kuhn (1962) and discuss whether GEOBIA can be regarded as a paradigm according to this definition. We crystallize core concepts of GEOBIA, including the role of objects, of ontologies and the multiplicity of scales and we discuss how these conceptual developments support important methods in remote sensing such as change detection and accuracy assessment. The ramifications of the different theoretical foundations between the ‘per-pixel paradigm’ and GEOBIA are analysed, as are some of the challenges along this path from pixels, to objects, to geo-intelligence. Based on several paradigm indications as defined by Kuhn and based on an analysis of peer-reviewed scientific literature we conclude that GEOBIA is a new and evolving paradigm.

https://escholarship.org/content/qt3r28w930/qt3r28w930.pdf?t=n18hz8

Geographic Object-Based Image Analysis - Towards a new paradigm.

Concepts and Foundations of Remote Sensing Elements of Photographic Systems Basic Principles of Photogrammetry Introduction to Visual Image Interpretation Multispectral, Thermal, and Hyperspectral Sensing Earth Resource Satellites Operating in the Optical Spectrum Digital Image Processing Microwave and Lidar Sensing Appendix A: Radiometric Concepts, Terminology, and Units Appendix B: Remote Sensing Data and Information Resources Appendix C: Sample Coordinate Transformation and Resampling Procedures

/pdf/remote-sensing-and-image-interpretation-1yb93lc9ws.pdf

Remote Sensing and Image Interpretation

Land evaluation for land use planning

A computer-based method for generating land use suitability evaluations for urbanizing areas is presented. These evaluations are based on an analysis of the physical characteristics of land, such as topography, soil class, soil drainage, flood hazard, and depth to bedrock. This method allows a great deal of flexibility in analysis and provides the ability to look at land use suitability from a variety of viewpoints or development policies. The use of this computer-based system to prepare residential land use suitability maps for a 59.5-km² (23.0-sq mile) area containing 5,950-ha (2.47-acre) data cells is illustrated. Such a method could be a powerful planning tool when used in conjunction with an evaluation of the other social, economic, political, and environmental factors that shape the patterns of urban development.

Computer-based land use suitability maps

A method for mapping the physical characteristics of land, and for applying this information to an evaluation of the suitability of the land in metropolitan fringe areas to urban development is presented. It is proposed that land use suitability maps be prepared for planning areas. These maps indicate the relative land use suitability of terrain units in the planning area by rating these units as optimum, satisfactory, marginal, or unsatisfactory for various land uses. The land use suitability maps are based on terrain maps drawn for the area and on land use suitability ratings prepared for the area. The land use suitability ratings are based primarily on the topography, soil, drainage, and depth to bedrock characteristics of land areas. Land use suitability maps should be used as a planning tool in conjunction with an evaluation of the other social, economic, political, and environmental factors that shape the patterns of urban development.

Terrain Analysis for Metropolitan Fringe Area Planning

Aerial photography has been used for nearly a century. Recent developments in aerial photography, such as color film, color infrared film, and multiband photographic systems, have greatly increased the amount of useful information obtainable from aerial photographs. Remote sensing instruments that operate in different parts of the electromagnetic spectrum from the human eye and photographic sensors can detect many things beyond the scope of human and photographic sensors. Thermal imagery can detect thermal pollution entering streams. Side-looking airborne radar can map terrain day or night, almost without regard for weather conditions. Remote sensing instruments having civil engineering applications are described herein. The emphasis is on photography, thermal imagery, multispectral imagery, and side-looking airborne radar. Applications of airborne remote sensing technology to soils mapping, water pollution detection and monitoring, and urban and regional planning are illustrated.

Ralph W. Kiefer

Papers

Remote Sensing and Image Interpretation

Land evaluation for land use planning

Computer-based land use suitability maps

Terrain Analysis for Metropolitan Fringe Area Planning

Applications of Airborne Remote Sensing Technology